Strategic Decision Making
Using Attributes to Predict Objectives in Preference Models
Decision Analysis
Generating Objectives: Can Decision Makers Articulate What They Want?
Management Science
Decision Analysis
Decision Analysis
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Real decision makers exhibit significant shortcomings in the generation of objectives for decisions that they face. Prior research has illustrated the magnitude of this shortcoming but not its causes. In this paper, we identify two distinct impediments to the generation of decision objectives: not thinking broadly enough about the range of relevant objectives, and not thinking deeply enough to articulate every objective within the range that is considered. To test these explanations and explore ways of stimulating a more comprehensive set of objectives, we present three experiments involving a variety of interventions: the provision of sample objectives, organization of objectives by category, and direct challenges to do better, with or without a warning that important objectives are missing. The use of category names and direct challenges with a warning both led to improvements in the quantity of objectives generated without impacting their quality; other interventions yielded less improvement. We conclude by discussing the relevance of our findings to decision analysis and offering prescriptive implications for the elicitation of decision objectives. In this version of the paper, “Improving the Generation of Decision Objectives” by Samuel D. Bond, Kurt A. Carlson, and Ralph L. Keeney, originally published online ahead of print March 10, 2010, the first panel heading of Figure 2 was corrected to read “Study 1 (Choice context = Dissertation),” as shown on page 243.